Photos | City View from a Store Window
A man sitting in a window looks out at the bustling city street filled with people, cars, and storefronts. The busy urban landscape creates a stark contrast to the stillness of the man sitting indoors, contemplating the world outside.
BLIP-2 Description:
a man sitting in a window looking out at a storeChronologically Adjacent
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Metadata
Capture date:
Original Dimensions:
640w x 480h - (download 4k)
Usage
Dominant Color:
tarmac lighting housing path machine shelter city urban outdoors potted intersection vehicle car license plant tree cafe lb shopping bicycle transportation storefront stop downtown cinema indoors accessories old sidewalk photography outdoor street diner road asr plate glasses building architecture food shop automobile office metropolis junglescene condo mall restaurant terminal walking bus land advertisement door nature neighborhood
Detected Text
date
2003-01-23T18:21:16-08:00
tzoffset
-28800
tzname
America/Los_Angeles
overall
(20.18%)
curation
(50.00%)
highlight visibility
(4.36%)
behavioral
(70.61%)
failure
(-0.83%)
harmonious color
(-0.97%)
immersiveness
(0.46%)
interaction
(1.00%)
interesting subject
(-73.44%)
intrusive object presence
(-32.50%)
lively color
(-8.74%)
low light
(67.97%)
noise
(-7.93%)
pleasant camera tilt
(-14.54%)
pleasant composition
(-85.01%)
pleasant lighting
(-59.52%)
pleasant pattern
(3.30%)
pleasant perspective
(-12.51%)
pleasant post processing
(5.85%)
pleasant reflection
(-2.21%)
pleasant symmetry
(0.46%)
sharply focused subject
(0.20%)
tastefully blurred
(-12.47%)
well chosen subject
(-15.64%)
well framed subject
(-38.06%)
well timed shot
(-0.34%)
all
(-10.96%)
* NOTE: This image was scaled up from its original size using an AI model called GFP-GAN (Generative Facial Prior), which is a
Generative adversartial network that can be used to repair (or upscale in this case) photos, sometimes the results are a little...
weird.
* WARNING: The title and caption of this image were generated by an AI LLM (gpt-3.5-turbo-0301
from
OpenAI)
based on a
BLIP-2 image-to-text labeling, tags,
location,
people
and album metadata from the image and are
potentially inaccurate, often hilariously so. If you'd like me to adjust anything,
just reach out.